Utilizing Smart Devices to Identify New Phenotypical Characteristics in Movement Disorders
- Conditions
- Essential TremorMovement DisordersParkinson DiseaseAtypical ParkinsonismParkinson's Syndrome
- Interventions
- Other: Data Capture
- Registration Number
- NCT03638479
- Lead Sponsor
- Universität Münster
- Brief Summary
This observational and experimental study seeks to establish a Smart Device System (SDS) to monitor high-resolution handtremor-based data using Smartphones, SmartWatches and Tablets. By doing this, movement data will be analyzed in depth with advanced statistical and Deep-Learning algorithms to identify new clinical phenotypical characteristics Parkinson's Disease and Essential Tremor.
- Detailed Description
Current smart devices as smartphones and smartwatches have reached a level of technical sophistication that enables high-resolution monitoring of movements not only for everyday sports activities but also for movement disorders. Tremor-related diseases as Parkinson's Disease (PD) and Essential Tremor (ET) are two of the most common movement disorders. Disease classification is primarily based on clinical criteria and remains challenging. The primary goal of this study is to identify new phenotypical characteristics based on the captured movement data by the tremor-capturing smartwatches and tablets and smartphone-based questionnaires.
The system will be applied and analyzed within an experimental and observational setting and only captures from patients, which have received informed consent. Within the study period, the SDS is not intended as clinical diagnostic support for physicians and will be not be used as medical device.
Recruitment & Eligibility
- Status
- COMPLETED
- Sex
- All
- Target Recruitment
- 513
- Diagnosed with Parkinson's Disease (ICD-10-GM G20.-) or Essential Tremor (G25.0)
- Comparison group: Other movement disorders including atypical Parkinsonian disorders and healthy participants
- Unable to obtain informed consent
- Skin-related conditions at one of the wrists or any other medical conditions that could harm the participant's health by wearing the smartwatch at both wrists.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description No Parkinson's Disease and No Essential Tremor Data Capture Participant's with no diagnosis of PD, ET or other Movement Disorders Parkinson's Disease Data Capture Participant's diagnosed with Parkinson's Disease Essential Tremor Data Capture Participant's diagnosed with Essential Tremor or other Movement Disorders
- Primary Outcome Measures
Name Time Method Acceleration data in all three axes (x,y,z) measured at both wrists via Smartwatches during 10 minutes of neurological examination. Aggregated data: Mean Frequency and Amplitude of Tremor. 2018-2020 The raw time series data (acceleration data) and the aggregated data will be analyzed to train a neural network to classify the participant's movement disorder.
- Secondary Outcome Measures
Name Time Method
Trial Locations
- Locations (1)
Institute of Medical Informatics, University of Münster
🇩🇪Münster, Germany